Genetic Mapping, Candidate Gene Identification and Marker Validation for Host Plant Resistance to the Race 4 of Fusarium oxysporum f. sp. cubense Using Musa acuminata ssp. malaccensis

Fusarium wilt of banana is a devastating disease that has decimated banana production worldwide. Host resistance to Fusarium oxysporum f. sp. Cubense (Foc), the causal agent of this disease, is genetically dissected in this study using two Musa acuminata ssp. Malaccensis segregating populations, segregating for Foc Tropical (TR4) and Subtropical (STR4) race 4 resistance. Marker loci and trait association using 11 SNP-based PCR markers allowed the candidate region to be delimited to a 12.9 cM genetic interval corresponding to a 959 kb region on chromosome 3 of ‘DH-Pahang’ reference assembly v4. Within this region, there was a cluster of pattern recognition receptors, namely leucine-rich repeat ectodomain containing receptor-like protein kinases, cysteine-rich cell-wall-associated protein kinases, and leaf rust 10 disease-resistance locus receptor-like proteins, positioned in an interspersed arrangement. Their transcript levels were rapidly upregulated in the resistant progenies but not in the susceptible F2 progenies at the onset of infection. This suggests that one or several of these genes may control resistance at this locus. To confirm the segregation of single-gene resistance, we generated an inter-cross between the resistant parent ‘Ma850’ and a susceptible line ‘Ma848’, to show that the STR4 resistance co-segregated with marker ‘28820’ at this locus. Finally, an informative SNP marker 29730 allowed the locus-specific resistance to be assessed in a collection of diploid and polyploid banana plants. Of the 60 lines screened, 22 lines were predicted to carry resistance at this locus, including lines known to be TR4-resistant, such as ‘Pahang’, ‘SH-3362’, ‘SH-3217’, ‘Ma-ITC0250’, and ‘DH-Pahang/CIRAD 930’. Additional screening in the International Institute for Tropical Agriculture’s collection suggests that the dominant allele is common among the elite ‘Matooke’ NARITA hybrids, as well as in other triploid or tetraploid hybrids derived from East African highland bananas. Fine mapping and candidate gene identification will allow characterization of molecular mechanisms underlying the TR4 resistance. The markers developed in this study can now aid the marker-assisted selection of TR4 resistance in breeding programs around the world.


Introduction
Bananas (Musa spp.) are an important horticulture crop, typically consumed as a fruit or staple food, and they are cultivated in the tropical and subtropical regions around the world. Musa spp. were domesticated in Southeast Asia and Melanesia, and hybridisation involving mainly A (Musa acuminata) and B (Musa balbisiana) genome progenitors gave rise to most of the domesticated forms of the dessert and plantain bananas we see today [1][2][3]. Musa acuminata have been divided into multiple subspecies [4,5], and hybridisation among them resulted in edible diploids. Restitution of the gametes at meiosis led to the formation of triploid cultivars [1,6,7].
Fusarium wilt of banana (FWB), also known as Panama disease, is one of the most devastating diseases affecting banana plants. The global epidemics owing to FWB have put major constraints on banana production both historically and at the present time [8,9]. The causal agent for this disease is the soil-borne fungus Fusarium oxysporum f. sp. cubense (Foc). Foc can be classified into a race structure, reflecting its banana host range [10][11][12][13] and unique vegetative compatibility groups (VCGs). Foc race 1 was the cause of the pandemic that decimated the triploid cultivar 'Gros Michel' (genome AAA) during the last century. Its replacement, the 'Cavendish' banana, is resistant to Foc race 1. Cavendish bananas are now the dominant cultivar on the market, accounting for more than 40% of the 124 M tonnes of world banana production in 2021 [14], with export markets accounting for approximately 15% of the total production [15].
During the 1990s, a previously unknown race, the tropical race 4 (TR4) of FWB, emerged and decimated Cavendish plantations around the world [16,17]. According to the range of the banana subgroups affected, TR4 strains are collectively classified by subtropical race 4 (STR4) as members of race 4. Vegetative compatibility grouping (VCG) and multi-loci molecular phylogeny have provided distinction between the two groups of isolates [11,13,18,19]. STR4 can infect Cavendish plants under subtropical conditions, whereas TR4 is virulent on all Cavendish and many other banana cultivars under both tropical and subtropical conditions [20]. So far, TR4 has significantly curtailed banana production in Australia [21], China [22], Indonesia [23], Malaysia [24], the Philippines [19,25], Jordan [26], Israel and other Middle East regions [27], India [28], Mayotte [29], and Africa [30] and has spread to locations as far as Colombia and Peru [31,32]. The disease poses a major threat to banana production, limiting the selection of cultivars and the land suitable for commercial production and, at the same time, putting constraints on food security of smallholders.
Foc infects banana plants through the roots then travels through the vascular vessels to colonise the rhizome and the pseudostem of susceptible plants [33,34]. Symptoms are manifested as localised necrotic lesions in and around the vascular vessels. Eventually the mycelia travel up through the xylem and establish themselves in the aerial parts of the plants. Extensive fungal colonisation blocks the water-conducting vessels of the xylem,  (A) Representative plants of six genotypes following infection with Foc-STR4. Foc-STR4-susceptible individuals 'Ma845', 'Ma846', and 'Ma848' displayed vascular wilting and plant death, and brown discolourations were associated with the colonisation of the fungus inside the rhizomes. The 'Ma850', 'Ma851', and 'Ma852' parents were completely resistant to Foc-STR4 and did not show any internal or external symptoms. (B) The development of Musa acuminata ssp. malaccensis populations used in this study. The 'R' progenitor is the original Foc race 4-resistant parent which gave rise after selfing to three F 1 plants, 'Ma850', 'Ma851', and 'Ma852', segregating for both Foc-TR4 and Foc-STR4 resistance. A susceptible 'S' progenitor, that was not related to the 'R' progenitor, gave rise to three self-crossed progenies, 'Ma845', 'Ma846', and 'Ma848', all of which were Foc race 4-susceptible. The genetic analysis carried out in this study used self-derived F 2 progenies of Ma851 and Ma852 as well as progenies derived from an inter-cross between the two (Population 1). The segregation of resistance was further validated using an inter-cross between 'Ma850' and 'Ma848' (Population 2). The F 2 line #5 from this cross was selfed to generate an F 3 population segregating for STR4 resistance. Rectangles indicate parental lines. Ovals indicate progenies derived from the same parent(s). Parents are coloured according to resistant (red) or susceptible (blue) Foc race 4 phenotypes. Progenies (ovals) are shaded blue to indicate the absence of resistance amongst all progenies tested or exhibit red/blue stripes to indicate the segregation of Foc race 4 resistance within the population. Solid lines indicate self-cross pollinations. A dashed line indicates an inter-cross.

Genetic Mapping
Population 1 was used for genetic mapping. Eleven CAPS markers were developed to anchor the region underlying the STR4 QTL (Table 1). The most proximal (27960) and distal (30000) markers defined a 1.45 Mb region in 'DH-Pahang' v4 ( Table 2). The markers are named according to their unique identifiers in 'DH-Pahang' v1, and their corresponding v4 gene models as well as their predicted proteins are listed ( Table 2). The 11 co-dominant CAPS markers were mapped in 435 F 2 individuals of Population 1. The genetic distance in centiMorgan (cM) was calculated as the number of progenies carrying a cross-over event between a pair of adjacent markers over the total number of individuals ( Figure 2). Overall, the order of the genetic linkage map was consistent with the physical positions of these genes on chromosome 3 in 'DH-Pahang' v4, indicating the absence of large structural rearrangements in this region between the parental M. acuminata ssp. malaccensis lines and 'DH-Pahang' v4. A set of 32 lines carrying crossover events in this region were phenotyped to further delimit this region ( Figure 3A). Resistance was completely dominant over susceptibility at this locus. Therefore, only recombinants carrying a homozygous-B to heterozygous-H (B/H) or a H/B cross-over were tested. Recombinants carrying A/H or H/A cross-overs were not tested, as 'A' cannot be differentiated phenotypically from 'H'. The recombinants were grouped according to their Foc-STR4 resistance and susceptibility ( Figure 3B). In the Foc-STR4-resistant phenotypic group, the three M. acuminata ssp. malaccensis parents, 'Ma850', 'Ma851', and 'Ma852', along with nine recombinants, showed resistant phenotypes that were clearly separated from the susceptible progenies by least significant difference (LSD) ( Figure 3B). Among them, the H/A recombinant line '18' showed a resistant phenotype, but it is not informative for individuals carrying homozygous alleles for resistance (A), as it cannot be differentiated phenotypically from the heterozygotes (H). On the other hand, 23 recombinants showed Foc-STR4-susceptible phenotypes ( Figure 3B). The susceptibility of these recombinants seemed to be highly elevated, with the majority of the clones exhibiting an RDI of 8 (plant death) by the time of harvest. The STR4 resistance locus is defined by three proximal recombinants (852-143, 852-168, and 4_16), with marker-phenotypes all suggesting that the locus is distal to marker 28420, and with four distal recombinants (852-7, 852-140, 852-162, and 81) collectively, suggesting that the locus is proximal to marker 29590 ( Figure 3A,B). This defined the locus within a genetic interval of 12.9 cM between 28420 and 29590 ( Figure 2). Furthermore, the marker phenotype of recombinant lines 194 and 852-108 indicated that the locus can potentially be refined to lie between markers 28820 and 29460 ( Figure 3A,B), although additional recombinant lines are required to validate this interval. However, eta-squared (η 2 ) values of marker-trait association are the highest at markers 28820 and 29460 (p = 0.05), confirming that they are positioned closest to the trait locus ( Figure 3A). Table 1. CAPS marker information. The numeric identifier in primer names corresponds to the gene models of 'DH Pahang' assembly v1 without the prefix 'GSMUA_Achr3G'. T is the annealing temperature used in the PCR. Frag or fragment denotes the PCR amplicon size in base pairs (bp). In the 'Cut sizes' column, lengths of the digested products are shown for the R and S marker alleles. Superscript 'm' indicates a monomorphic SNP cutting site. The SNP position (R to S nucleotide change) is calculated from the predicted translation start site AUG or 'ATG' in the genomic sequence of 'DH-Pahang' v4 gene models (SNP ATG ).  developed disease over the total number of clones (n) screened per genotype) between 20-100%. All critical recombinant phenotypes (except 852-7) were correctly associated with the direction of the trait locus between 28420 and 29590 ( Figure 3A,C). The recombinants 194 and 852-108 also showed the expected association, with the closest flanking markers 28820 and 29460. Likewise, this region was also associated with the highest η 2 values, at 0.17-0.18, p = 0.1 ( Figure 3A). The phenotypic variation explained by TR4 at this locus was smaller than that controlled by STR4 (η 2 : 0.68-0.73).  × 'Ma852' and the inter-cross of 'Ma851' × 'Ma852', collectively referred to as Population 1. The candidate region is mapped to a 12.9 cM genetic interval between markers 28420 and 29590. The Foc-STR4/Foc-TR4 resistance locus is highlighted in red. This locus is defined by multiple critical lines carrying recombination events between markers 28420 and 28820 and between markers 29460 and 29590. The markers most closely linked to the locus are 28820 and 29460. The directions of the marker-trait association are indicated with an arrow. All lines were tested against Foc-STR4. Asterisks (*) indicates that these lines were additionally tested against Foc-TR4. Plus (+) indicates that the Foc-TR4 phenotype of this line was not in agreement with all the other lines tested at the same recombined position. screened per genotype on a scale at the top. Asterisks (*) indicate that resistance was observed where a susceptible phenotype was expected. The respective +/− controls in the Foc-TR4 screening were the Cavendish cultivar Williams with or without the pathogen. RDI was scored according to a 1-8 scale [33] for Foc-STR4 and a 1-6 scale for Foc-TR4 [28]. The 95% confidence intervals of the means are plotted as error bars for lines with n > 2. Significant differences at p < 0.05 among groups were determined using one-way ANOVA. The means were separated by least significant difference at p ≤ 0.05. The subsets are indicated by letters in superscript.
TR4 phenotyping of a subset of critical recombinants produced a similar result ( Figure 3C). The rhizome discolouration was scored on a scale of 1 to 6, with 1 corresponding to a healthy plant, and 2 through 6 corresponding to the proportion of discoloured rhizomes of ≤20%, ≤40%, ≤60%, ≤80%, and ≤100%, respectively. The phenotypic difference between the R and S recombinants were reduced in comparison with the STR4 phenotype ( Figure 3C). The marker-defined susceptible lines were generally more resistant to TR4 than to STR4, with more clones per line that did not show any rhizome discolouration. The positive control 'Williams' showed an average RDI of greater than 60%, indicating that the inoculation method worked as intended. Separation of the means using Duncan's multiple range test produced subsets that were more overlapping than those of STR4. Two S recombinants, 852-7 and 852-47, did not produce the expected symptoms, and their means were clustered together with the resistant recombinants and the uninoculated Williams ( Figure 3C). This suggests that sensitivity to TR4 in M. acuminata ssp. malaccensis was not optimally detected at the current inoculum dosage. However, all susceptible recombinants except 852-7, 852-47, and 1 showed a disease incidence (number of plants that developed disease over the total number of clones (n) screened per genotype) between 20-100%. All critical recombinant phenotypes (except 852-7) were correctly associated with the direction of the trait locus between 28420 and 29590 ( Figure 3A,C). The recombinants 194 and 852-108 also showed the expected association, with the closest flanking markers 28820 and 29460. Likewise, this region was also associated with the highest η 2 values, at 0.17-0.18, p = 0.1 ( Figure 3A). The phenotypic variation explained by TR4 at this locus was smaller than that controlled by STR4 (η 2 : 0.68-0.73).

Candidate R Gene Expression Profiling
A set of 24 Population 1 progenies that are homozygous for the resistant 'A' or susceptible 'B' for all eleven markers across this region were used to perform a transcriptome analysis with RNAseq. The phenotype of each of these lines was confirmed in a pot trial prior to the start of this experiment. The experiment was designed to identify a narrow transcriptome response that is specifically controlled by the resistance locus in this region. Genetic effects unlinked to this locus are accounted for by the segregation of these genes in the genetic background.
Our previous study identified multiple classes of R genes present in the candidate region [57]. Differential gene expression analysis was performed in a pairwise (R vs. S) manner at four time points, namely 0, 1, 3, and 7 days post-inoculation (dpi). Markers 28420 and 29590 flanked a 959 kb region containing 125 predicted gene models in 'DH Pahang' v4 (Table S1). Gene Ontology (GO) enrichment analysis of this region revealed two significantly enriched GO terms (p-adj. < 0.05) that were associated with plant defense under the ontology of 'Biological Process', namely 'defense response to bacterium' (GO:0042742, 7 genes) and 'defense response to fungus' (GO:0050832, 5 genes) (Table S2). Under 'Molecular Function', GO terms were significantly enriched for 'polysaccharide binding' (GO:0030247) and 'endoribonucleae activity' (p-adj. < 0.05).
Of all the R genes predicted in this region, seven genes showed differential expression profiles between R and S at two or more time points at p-adj. < 0.05 ( Figure 4). Of the four receptor-like proteins (RLP), expression of 31310 and 31470 was upregulated at 1 and 3 dpi in R progenies before being downregulated at 7 dpi, although it remained relatively low in the S progenies throughout the time course ( Figure 4A,B). Transcript levels of the RLP 31460 were significantly higher in R relative to S at all time points (p-adj. < 0.05) ( Figure 4C). The transcript levels of 31460 steadily declined from 0 to 3 dpi in R but were maintained at a higher level in R than in S across all time points. In contrast, transcripts of the RLP 31380 were readily downregulated at 1 dpi before a slight recovery at 3 and 7 dpi in both S and R progenies and with R transcripts significantly higher (p-adj. < 0.01) than S transcripts at 1 dpi ( Figure 4D). The receptor-like protein kinase (RLK) 31320 showed a similar profile to RLP 3130 and 31470 in that Foc-STR4 rapidly induced an expression peak at 1 dpi, followed by a gradual downregulation at 3 dpi before returning to a pre-treatment level at 7 dpi ( Figure 4E). The 31320 transcripts in S genotypes were maintained at a low level throughout the experiment. Transcript levels of the other RLK gene 32220, a LRK10L homolog, were significantly upregulated at 1 dpi in R and were then upregulated further at 7 dpi ( Figure 4F). Its transcripts in S remained relatively low at all time points. The cysteine-rich protein kinase (CRK) 31510 had an expression peak at 3 to 7 dpi in R before a sharp downregulation to a level comparable to the control at 7 dpi ( Figure 4G). Again, the S transcripts were maintained at a relatively low level. Lastly, the serine/threonine protein kinase (STK) 32050 showed a strong downregulation in R across all time points ( Figure 4H), whereas the S transcripts started at a similar level to R but were gradually upregulated at 1 to 3 dpi before returning to a pretreatment level at 7 dpi. No intracellular R proteins were differentially expressed at more than two time points between R and S in this region.

Foc-STR4 Resistance and Marker Validation in Population 2
The haplotype analysis across the QTL region showed that the marker loci were all heterozygous in the R parents and were susceptible 'B' haplotype interrupted by heterozygous segments in the S parents ( Figure 5A). The candidate region 'B' for susceptibility defined by 28820/29460 in the S parents was flanked by heterozygous segments at the proximal (28220-28420) and distal (29590-29670) ends ( Figure 5A). Therefore, the marker haplotypes of the S parents were consistent with the location of the STR4/TR4 locus as defined by Population 1.

Foc-STR4 Resistance and Marker Validation in Population 2
The haplotype analysis across the QTL region showed that the marker loci were all heterozygous in the R parents and were susceptible 'B' haplotype interrupted by heterozygous segments in the S parents ( Figure 5A). The candidate region 'B' for susceptibility defined by 28820/29460 in the S parents was flanked by heterozygous segments at the proximal (28220-28420) and distal (29590-29670) ends ( Figure 5A). Therefore, the marker haplotypes of the S parents were consistent with the location of the STR4/TR4 locus as defined by Population 1. To validate the segregation of resistance observed in Population 1, 38 F2 progenies of the 'Ma848' × 'Ma850' cross were screened for STR4 resistance ( Figure 5B). There were 16 R and 22 S phenotypes observed, while the parents, 'Ma848' and 'Ma850', showed the expected STR4 susceptibility and resistance, respectively. The mapping of 28820 in the F1 individuals showed that the dominant allele of 28820 closely segregated with resistance ( Figure 5C). Decoupling of the marker with the trait occurred in F2 individuals '16' and '34', suggesting that recombination occurred between the resistance gene and the marker locus. An F3 population was developed using a self-cross of the STR4-resistant F2 individual '5'. Of the 102 F3 individuals screened for STR4 resistance, 67 individuals were resistant (mean RDI < 4), and 35 individuals were susceptible (mean RDI ≥ 4) ( Figure 5D), with goodness-of-fit statistics showing significant deviation from an expected segregation ratio of 3 R:1 S (χ 2 = 4.71, p = 0.029, df = 1, α = 0.05).  Foc-STR4-resistant and -susceptible phenotypes are differentiated by red/blue coded bars, respectively. RDI: rhizome discolouration index. The line (number 5) with red highlighting was used to generate the self-crossed F 2 population. (C) A CAPS marker screening was performed on the 'Ma850' × 'Ma848' F 1 individuals using the primers '28820-SNP8-F2' and '28820-SNP8-R1', targeting an SNP in gene model GSMUA_Achr3G28820 ('DH-Pahang' v1.0) and PCR conditions as described in Table 1. The dominant band (544 bp) after a BstZ17I digest is associated with Foc-STR4 resistance. Yellow arrows indicate de-coupling of the dominant marker band with Foc-STR4 resistance. (D) 'Ma850' × 'Ma848' F 2 individuals screened with Foc-STR4. Individuals with an RDI score of < 4 are considered resistant (R), and those with an RDI score of ≥ 4 (greater than 20% discolouration) are considered susceptible (S). Individual x-axis labels are staggered every two lines. The number of clones (n) tested per line is indicated in brackets.
To validate the segregation of resistance observed in Population 1, 38 F 2 progenies of the 'Ma848' × 'Ma850' cross were screened for STR4 resistance ( Figure 5B). There were 16 R and 22 S phenotypes observed, while the parents, 'Ma848' and 'Ma850', showed the expected STR4 susceptibility and resistance, respectively. The mapping of 28820 in the F 1 individuals showed that the dominant allele of 28820 closely segregated with resistance ( Figure 5C). Decoupling of the marker with the trait occurred in F 2 individuals '16' and '34', suggesting that recombination occurred between the resistance gene and the marker locus. An F 3 population was developed using a self-cross of the STR4-resistant F 2 individual '5'. Of the 102 F 3 individuals screened for STR4 resistance, 67 individuals were resistant (mean RDI < 4), and 35 individuals were susceptible (mean RDI ≥ 4) ( Figure 5D), with goodness-of-fit statistics showing significant deviation from an expected segregation ratio of 3 R:1 S (χ 2 = 4.71, p = 0.029, df = 1, α = 0.05).

Discussion
Conventional breeding is typically constrained in banana because polyploid cultivars are sterile and parthenocarpic [64]. Development of large segregating populations can be achieved using highly fertile banana diploids. The underlying genetics in banana are still challenging due to their long growth cycles, the logistics of performing high-throughput screenings, and the high variability in the phenotypic data, as reflected in this study. Despite these difficulties, the availability of the Musa draft genome assemblies and lower whole genome genotyping/sequencing costs have facilitated studies in SNP discovery, genome evolution, and population genetics in banana [65][66][67][68][69]. With Foc-TR4 edging closer to the major banana growing regions of Latin America [70], it becomes ever more important to dissect host resistance against Foc-TR4 and, in doing so, to identify potential resistance genes that underpin the Foc-TR4 resistance per se. This would allow resistance to be deployed in elite cultivars by gene editing or through a transgenic approach. Molecular markers that are closely linked to TR4-resistant QTLs can fast-track resistant alleles in banana-breeding programs.
By using transcriptome sequencing on S or R progenies carrying contrasting haplotypes in the QTL region, candidate R genes underlying resistance were identified. Segregant analysis is a powerful approach when combined with the positional information from genetic mapping. Firstly, the candidate region was confirmed in Population 1. The marker haplotype in the susceptible parents and the segregation of Foc-STR4 further independently confirmed the candidate region in Population 2. The closely linked marker 28820 segregated with STR4 resistance, although not completely, but the phenotypic variation explained at marker loci 28820 and 29460 was the highest in this genetic interval for both STR4 and TR4. Within this region, 32220, a leaf rust 10 disease-resistance locus receptor-like protein kinase-like protein 2.1 (LRK10L-2.1) was related to the wheat LRK10 gene [71]. Transcripts of 32220 were gradually and consistently upregulated in R progenies during the time course, peaking at 7 dpi. This response was not detected in the S progenies. The 32220 predicted protein belongs to the LRK10L-2 subfamily of receptor-like kinases [72,73] and has a cysteine-rich ectodomain, a transmembrane domain, and a predicted intracellular serine/threonine kinase at its C-terminus. Members of this class of RLKs have been shown to be important for mediating resistance responses to stripe rust fungus and powdery mildew in wheat [74,75], and they are involved in ABA-mediated signaling and drought resistance in Arabidopsis [76].
The genetic Interval closest to the STR4 resistance locus is between 28820 and 29590. It is not well-defined at this stage. Only two individuals were identified with crossovers between these markers. More recombinants are needed to narrow this interval more precisely. In the larger region between markers 28840 and 29590, multiple recombinants consistently confirmed the direction of the trait locus on either side. Although one critical recombinant (852-7) did not produce any symptoms in the TR4 screening, the phenotypic data were generally concordant with the genetic interval defined for both STR4-and TR4resistant loci. Within this interval, there was a cluster of receptor-like kinases (LRR XII subfamily) and receptor-like proteins (LRR RLP subfamily) positioned in an interspersed arrangement [57]. They, respectively, belong to the LRR XII and LRR RLP subfamilies of pattern recognition receptors [72,77]. Two RLPs showed a very rapid upregulation of transcripts at 1 dpi, consistent with their roles in the recognition of pathogen effectors at the onset of infection [78]. These RLPs are similar to the tomato LeEIX1 and LeEIX2 resistance proteins that directly interact with an ethylene-inducible xylanase (Eix) effector protein from Trichoderma viride [79]. Similarly, an Eix-like effector (VdEIX3) from Verticillium dahlia was recognised by the Nicotiana benthamiana LRR RLP NbEIX2 [80], inducing an innate immunity response and increasing the resistance to other oomycete and fungal pathogens in N. benthamiana.
A gene encoding a cysteine-rich protein kinase was also strongly upregulated during the onset of infection in the R but not in the S genotypes. Cysteine-rich protein kinases contained DUF domains and a kinase domain. Such genes have been found to confer resistance against Septoria tritici blotch and leaf rust in wheat [81,82]. Overexpression of an Arabidopsis CRK homolog led to enhanced resistance against Pseudomonas syringae [83]. In addition, an LRR RK gene (Macma4_03_g31320.1) was differentially expressed between the S and R genotypes and exhibited an expression peak at 1 dpi in R, similar to the profiles of the three LRR RLPs. Plants, in general, have an abundant amount of RLKs and RLPs as part of their surveillance system to cope with the evolution and detection of pathogens [84]. The LRR ectodomain of pattern recognition receptors binds to proteins and peptides through pathogen-associated molecular patterns (PAMPs) or damage-associated molecular patterns (DAMNs) and is important for the recognition function. In Arabidopsis, FLAGELLIN SENSING2 (FLS2) recognises an elicitor epitope from the bacterial flagellin [85], and PEP RECEPTOR 1 (PEPR1) and PEPR2 recognise plant elicitor peptides, or peps, to activate a defense against Pythium irregulare [86,87]. In rice, LRR RK Xa21 recognises a highly conserved protein, RaxX, from Xanthomonas species to trigger immune responses [88].
Overall, there are multiple resistance genes differentially expressed between the S and R banana progenies with similar temporal expression profiles. All of them are indicative of a rapid response in the induction of resistance gene transcripts at the onset of STR4 infection. This suggests that these genes may act in close proximity to one another or even belong to the same gene network. Co-expression gene networks will be constructed from RNA sequencing data to identify co-expression modules. This information can then be integrated with the QTL region to characterize the candidate genes [89].
In this study, we demonstrated that SNP loci/trait associations can produce markers useful for marker-assisted selection. Unlike traditional bi-parental mapping, the wild subspecies of Musa are highly heterozygous, which render it challenging for genetics to be undertaken. The resistance source identified in this population was dominant, which is consistent with the mode of inheritance of a race 1 and, to a lesser extent, TR4-resistant QTLs located on chromosome 10 of a different Musa acuminata ssp. malaccensis [54]. The dominance of these loci can offer full TR4 protection, which is a desirable genetic solution to the TR4 pandemic since only one copy of the gene(s) is required to confer full resistance against TR4/STR4. Resistances that are not completely dominant may not be useful since partial resistance cannot offer protection against TR4 in the long term [90].
In marker-assisted selection, we used a marker closely linked to the resistance locus to detect lines potentially carrying this locus from several germplasm collections. Initial screening clearly suggested that this marker could identify some of the resistant individuals in the diploid collection, specifically detecting resistance in wild relatives or derivatives of M. acuminata ssp. malaccensis origin ( Figure 6, Table 3). The power of detection did not extend to other M. acuminata subspecies or derivatives that were not of M. acuminata ssp. malaccensis origin. This was evident in that this marker failed to detect resistance in the M. acuminata ssp. banksii collection (Table S4). Furthermore, the M. acuminata ssp. burmannica genotype 'Calcutta 4' has been reported to be highly resistant not only to STR4/TR4 [33,43] but also to the Sigatoka leaf spot disease [91]. 'Calcutta 4', as a source of resistance, has already been used extensively in IITA-NARO's breeding program. It was used as a male parent to derive seven tetraploid 'Matooke' hybrids, which were used to derive the triploid 'Matooke' NARITAs [92,93] (Table S3). Despite being TR4-resistant, 'Calcutta 4' was not detected as resistant in the marker screening in our study. Taken together, this highlights the presence of other sources of resistance in the germplasm collection as well as the limitation of this marker to detect resistance sources outside of M. acuminata ssp. malaccensis, possibly reflecting the phylogenetic divergence of the M. acuminata subspecies in the core Musa collection [59]. Overall, the marker was positive in 35 of 72 individuals in the IITA collection, exhibiting a detection frequency of 47.9%. This predicted that the chromosome 3 resistance source was already present in the IITA-NARO's breeding program.
The genotype screen also produced consistent results in the diploids, specifically 'Pahang', 'DH-Pahang', and 'Malaccensis-ITC0250'. These are known TR4/STR4-resistant genotypes. In the hybrids, 'SH3362' and 'SH3217', are positives for the dominant band. 'SH3362' was derived from crossing 'SH3217' and 'SH3142', with the latter derived from a cross between two cultivars of 'Pisang Jari Buaya' 'https://www.promusa.org/NARITA+ 16' (accessed on 12 March 2023). Despite being resistant to TR4, 'Pisang Jari Buaya' was a negative in our marker screen. The parentage of 'SH3217' can be further traced back to a cross between 'SH2095' and 'SH2766'. 'SH2095' was derived from a cross between 'Sinwobogi' (AA) and 'Tjau Lagada' (AA), whereas 'SH2766' was derived from 'Tjau Lagada' (AA) and the progeny of a cross between M. acuminata ssp. malaccensis and 'Guyod' (AA) 'https://www.promusa.org/NARITA+16' (accessed on 12 March 2023). Therefore, the source of resistance potentially can be traced back to a M. acuminata ssp. malaccensis origin, although validation is not possible without these progenitors or their DNA. 'SH3362' and its progenitor 'SH3217' were the male parents of 13 hybrids in the IITA collection (Table S3). Ten of these thirteen hybrids were heterozygous for the STR4/TR4 marker locus. Despite the common presence of this resistance source in the IITA-NARO's breeding program, further phenotypic screening in the IITA germplasm is required to validate this marker. Breeding programs around the world can now use this as a tool to identify potential TR4-resistant genotypes in their collections. This is a first-ever report on PCR-based markerassisted selection in a banana-breeding program. It will assist efforts towards curbing the TR4 pandemic.
The genetic mapping using 435 individuals of Population 1 delimited the QTL to a 959 kb region containing 125 predicted gene models between 28420 and 29590 in 'DH Pahang' v4 (Table S1). Due to the sheer volume of the population and the number of clones that would have to be multiplied in vitro, phenotyping the entire population was never the goal. A targeted strategy was used to define the QTL region, and only recombinants were tested. It allowed 'walking' along the chromosome to define the direction of the marker-trait association. Validation was achieved through testing multiple independent recombinants defining a single marker interval. Technical bottlenecks included slow multiplication of clones in the diploid (AA) lines, as they sometimes have reduced shoot proliferation potentials compared with the triploids. Furthermore, the dominant mode of inheritance means that phenotypic distinction can be made only between H/A and B and vice versa. Individuals containing cross-over events between A and H marker alleles cannot be used unless progeny testing is performed at the next generation. Important A/H recombinants can be tested this way, although it is a labor-intensive task.
Given that it takes 3 months for sufficient clones to be multiplied, 1 month for the plants to be hardened off in a glasshouse, and an additional 3 months post-inoculation for symptoms to develop, this type of screening where genotypes are consistently processed in batches in an optimized and high-throughput manner is just not achievable with field-based trials. Future work will focus on optimizing high-throughput setups in glasshouses [94] or growth chambers where relatively young plants in small pots and trays can be screened with Foc. Screening in a controlled environment can reduce variance in the symptoms. Lab-based soil-free hydroponic systems have been explored for TR4 screening [95,96] and have been used to assay Fusarium root rot in other plant species, such as alfalfa [97]. Highthroughput screening methodology from other plant/Fusarium pathosystems, such as Medicago truncatula/F. oxysporum f. sp. medicaginis, can potentially be adopted to screen for TR4 resistance in banana seedlings [98].
The STR4 screening produced clear-cut phenotypic differences between resistant and susceptible individuals. A hybrid inoculation method was used with spore suspension and an extra layer of millet added on top of the soil. This was implemented to increase the inoculum dosage and achieve uniformity with the infection. This allowed genotypic sensitivity to Foc to be detected reliably and the genetic interval to be defined. The TR4 screening also produced consistent results and identified the same genetic interval, although the plants, in general, did not produce symptoms as severe as STR4. The TR4 symptoms were slow to manifest, indicating that M. acuminata ssp. malaccensis were generally more resistant to TR4 than to STR4 in pot trials. The weaker correlation could be due to the presence of the chromosome 10 QTL for TR4 resistance in a fixed state in our resistant parents [54], which may also explain the segregation distortion we observed in the analysis of the F 3 progenies from Population 2. Image-based detection of symptoms can assist in the quantification of rhizome discolouration [40]. The issue with the TR4 screening was not the subtle differences in the level of discolouration but rather obtaining false negatives when symptoms were expected. Symptom severity was able to be elevated by an increase in the inoculum dosage. That, in turn, reduced the variance in the symptom development. Overall, this highlights the challenge of detecting a plant's sensitivity to Foc in a reliable manner.

Fungal Isolates
For the Foc-STR4 screening, three monoconidial VCG0120 isolates (BRIP63488, BRIP43781, and BRIP42331) from the Queensland Plant Pathology Herbarium were used as a combined

Foc-STR4 Pot Trial
Foc-STR4 pot trials were conducted in temperature-controlled glasshouses at the University of Queensland, St Lucia campus, QLD, Australia. The temperatures were controlled at 26 • C day/22 • C night for the entire duration of the experiments. Humidity was maintained at 60%. The amount of 50mL of 2.0 × 10 6 conidia/mL solution was poured directly into potted plants with a stem height of 30 cm, followed by spreading a layer of Foc-STR4-infested millet (20-30 g) on the surface of the soil. Protocols for preparing Foc-infested millet and conidia suspensions were previously described [33,99]. The soil surface was then topped with a thin layer of potting mix. The plants were watered lightly. Internal disease symptoms were scored 3 months post-inoculation. A 1-8 rhizome scale was used to score internal rhizome discolouration [33].

Foc-TR4 Pot Trial
Foc-TR4 pot trials were performed in a quarantined glasshouse at the University of Stellenbosch. Plants were hardened off for 2-3 months before the screening. The experimental setup for the pot trial was as previously described [100]. A millet inoculation technique was used, and disease incidences and internal discolouration of the rhizome (1-6 scale) were scored as per a previous study [101]. The positive and negative controls were uninoculated and Foc-TR4-inoculated Williams, respectively.

DNA Extraction and PCR
DNA extraction was performed using a hexadecyltrimethylammonium bromide (CTAB)-based method [106], with modifications as follows: At the washing step, the DNA pellet was washed three times with 8 mL of 70% ethanol to reduce residual salt contaminants and finally resuspended in 400 µL of nuclease free water. The DNA was quantified on a NanoDrop UV/Visible spectrophotometer for a single absorbance peak at 260 nm, with a 260 nm/280 nm absorbance ratio of 1.8 to 2.0. DNA was then checked using the broad-range Bradford assay on a Qubit machine and finally visualised on a 0.7% (w/v) agarose gel to check for band shearing and/or contamination with either RNA or polysaccharide.
PCR was performed using 80-100 ng of DNA template and Dreamtaq (Thermo Fisher Scientific, Waltham, MA, USA). Running conditions were set according to the manufacturer's recommendations. The primers and the corresponding annealing temperatures were optimized (Table 1). Forty cycles of PCR were used per reaction. Restriction enzyme digest was performed on 10 µL PCR product and 2 µL enzymatic mix consisting of 2 units of the enzyme and an appropriate 10× buffer ( Table 1). The digested products were visualised on a 2% agarose gel with a 1 Kb ladder (New England Biolabs, MA, USA). The markers were scored in a co-dominant manner, with restriction band patterns differentiating one homozygous allele from the other. The heterozygotes contained both allelic forms.

Digital Gene Expression Analysis on Candidate Genes
A transcriptome study was performed by using 12 R and 12 S progenies from Population 1. These progenies were tested against STR4, and their resistance/susceptible phenotypes were confirmed prior to the start of this experiment. A root-dipping method using Foc spore suspension was used to inoculate the plants [33], and whole roots in triplicates (n = 3) were harvested at 0, 1, 3, and 7 days post-inoculation (dpi). Samples were snap-frozen in liquid nitrogen and then ground to powder using a mortar and pestle. Spectrum TM Plant Total RNA kit (Sigma-Aldrich, MO, USA) was used to extract RNA. Here, 24 cDNA libraries corresponding to the R and S progenies harvested at the 4 time points were prepared and then sequenced using the Hiseq 4000 platform (Genewiz, Suzhou, China), generating approximately 48 Mb of 150 bp paired-end reads for each sample. Adaptor sequences and low-quality reads were filtered out using 'Fastp' [107]. Clean paired-end reads were then aligned to 'DH-Pahang' v4 reference genome using 'STAR' v2.7.10a and default parameters for all except '-outFilterMismatchNmax 6' and '-alignIntronMax 10000' [108]. Non-normalized read counts were tabulated with 'Feature-Counts' software (option: -M -g ID -t gene -p) [109] and then normalised to account for differences in sequencing depth among samples using the median-of-ratios method [110]. This value was calculated as the gene counts divided by a size factor specific to a sample, determined by the median ratio of gene counts relative to geometric mean of the gene counts per gene. DEGs were identified from pairwise comparisons between resistant and susceptible progenies at each time point using the 'DESeq2' R package [111]. Multiple testing was corrected using the Benjamini and Hochberg method [112]. The p-values were adjusted (p-adj.) to have a false discovery rate (FDR) cut-off of 0.05.

Statistical Analyses
The statistical software SPSS v28.0.1.0 (142) (IBM Corp., Armonk, NY, USA) was used to perform the statistical analysis described in this study. One-way ANOVA was performed in a pair-wise manner, with phenotype set as a dependent variable and marker-defined genotypes (B/H) as factors, to compare the means of STR4 and TR4 sensitivity at these loci. Any 'A' alleles were considered as 'H' for the purpose of statistical analysis, as resistance is completely dominant over susceptibility at this locus. The eta-squared (η 2 ) values on the phenotype were estimated on the basis of the fixed-effects model and reflected the phenotypic variation explained at each marker-defined locus. To analyze the STR4 and TR4 phenotypes of the recombinants, Waller-Duncan's multiple range testing was performed as a post hoc test to separate the means of the recombinants into subsets by least significant difference (LSD). Recombinants with n < 2 were excluded from the analysis. The harmonic mean sample size was estimated and used to account for the unequal variances associated with the uneven sample sizes (n) of the recombinants. The type 1/type 2 error seriousness ratio (k-ratio) was set to 100 (α = 0.05).

Conclusions
This study is the first-ever report of marker-assisted selection of STR4-and TR4resistant Musa accessions. The availability of molecular makers closely linked to the resistance locus can now facilitate the rapid screening of potentially TR4-resistant genotypes and thereby reduce the generation time required for phenotypic and field trials. However, this marker can detect resistances originating from M. acuminata ssp. malaccensis at this locus only. Given the prevalence of TR4 now threatening the entire banana industry worldwide, identification of candidate receptors, such as proteins and kinases with strong transcriptional evidence linking them to resistance at this locus, provides the first step towards molecular dissection of resistance mediated by these R genes in banana.
Supplementary Materials: The following supporting information can be downloaded at: https: //www.mdpi.com/article/10.3390/pathogens12060820/s1, Table S1: 'DH Pahang' v4 gene models within the candidate region; Table S2: Enrichment of Gene Ontology (GO) terms detected in the candidate region using p and q cutoffs of 0.05 and 0.1, respectively; Table S3: Screening of the IITA germplasm collection (Uganda) using the A-genome-specific marker 29730-A; Table S4:   Data Availability Statement: All data analysed during this study are included in this article and its supplementary files. The RNAseq data described in this study are available on request from the corresponding author. They are not publicly available due to confidentiality of genetic information pertaining to the gene discovery.